Method for analysing a wireless link of a wi-fi node, respective circuit performing the method, and application

ABSTRACT

A method for analyzing a wireless link (3) of a wireless node of a customer premises equipment (CPE) device (1) during operation of the CPE device comprises: performing an active test, during which a data transmission is forced through the wireless link, to obtain a first set of parameters, and performing before or after the active test a passive test, which is a monitoring ode during which a data transmission of the CPE device is monitored, to obtain a second set of parameters. In particular, based on the first set of parameters, it is determined whether and to which extent the wireless link is in an uncertainty zone, and based on the second set of parameters, the decision is made to assign an observed decrease in a measured data rate to physics effects or to interference effects.

TECHNICAL FIELD

The present disclosure relates to the field of wireless nodes andrespective devices communicating with each other via a wirelesscommunication.

BACKGROUND

Access gateways are widely used to connect devices in a home to theInternet or any other wide area network (WAN). Access gateways use inparticular digital subscriber line (DSL) technology that enables a highdata rate transmission over copper lines or optical lines. Residentialgateways, as well as other devices such as routers, switches, telephonesand set-top boxes, are understood in this context as customer premisesequipment (CPE) devices.

Access gateways including wireless technology have a key role in today'shome and professional environments. A mechanism for connecting wirelessdevices to a local area network (LAN) is called Wi-Fi, which is a brandname of the Wi-Fi Alliance for devices using the IEEE 802.11 family ofstandards for wireless data transmission. The IEEE 802.11 standardsdefine two types of wireless nodes, a general wireless device that canconnect to other devices called a station (denoted as STA) and a specialtype of a STA that is in control of the network, namely an access point(denoted AP). A Wi-Fi network, often called a WLAN (wireless local areanetwork), consists of an AP with one or several STA connected to the AP.

Due to its flexible and “invisible” nature, a lot of LAN applicationsare utilizing Wi-Fi rather than the classical wired Ethernet approach.This widespread usage of wireless LAN has exposed however a seriousdownside of using a shared medium technology: interference.Interference, both Wi-Fi and non-Wi-Fi related, leads to a degraded userexperience due to the nature of IEEE 802.11. In its most common form,IEEE 802.11 networks apply a medium access method in which collisionsare avoided by sensing that the medium is used (denoted as CSMA-CA). Themedium access method is also commonly known as “listen before talk”,describing the essence of the method and is referred to as “ClearChannel Assessment” (CCA). Clear channel assessment determines whether awireless communication channel is “occupied”, e.g., “busy” with anotherwireless communication and/or has an amount of interference that makesthe wireless communication channel unsuitable for communication. In thisway, it is determined whether the wireless communication channel isavailable or not available for communication, e.g. occupied or notoccupied.

Another impact of interference can be packet loss at the receiver side,leading to a reduction of the physical layer rate. The physical layerrate, also referred to in the following as “TrainedPhyRate” ormodulation rate, relates to the transfer rate on the physical layer ofthe wireless connection. The IEEE 802.11 MAC protocols use rateadaptation mechanisms for evaluating the properties of the wirelesschannel and select an appropriate physical layer rate. In this case, theinterference is not detected by the CCA of the transmitter, but isdecreasing the SINR (Signal to Noise and Interference Ratio) of theWi-Fi packets as seen by the receiver. Typically, Wi-Fi nodes will reactto packet loss by lowering the physical layer rate used towards a morerobust—but slower—physical layer rate in an attempt to increase thechance of successfully transmitting packets.

Therefore, in certain circumstances, the Wi-Fi connection can sufferfrom poor performance and even connection loss. Some of thesecircumstances are obvious and easy to explain to an end user. Forexample, if the distance between the station and the AP is too large,then signal levels are low and performance will degrade. Othercircumstances are “invisible” and not understood by the end user, e.g. ahidden node. A hidden node is invisible to some of the nodes of anetwork, leading to a practical failure of the CSMA-CA method, which cancause packet collision/corruption over air. In many cases, the end useris not able to diagnose the problem source and correct the issue.

For in-home Wi-Fi networks, connectivity and performance issues arecorrespondingly one of the main Internet service provider support costsand causes for help-desk calls. Today's focus for operators is mainly onWi-Fi network installation, associating a station with an AP. Internetservice providers are therefore searching for ways to get a betterunderstanding of the end user's wireless environment including linkquality and performance.

The ideal way to analyze Wi-Fi issues, e.g. connection setup,interference, throughput, etc., is by looking into the master node ofthe wireless LAN, namely the AP. The AP, as defined in IEEE 802.11,controls the network, hence all data and network control is visible bythe AP. The AP today can deliver statistics regarding packettransmission and signal levels. But the real issue why a link is droppedor why throughput is low, remains hidden to the internals of the AP.Today, at best an AP can deliver statistics but no view on what isactually happening in the wireless network.

Wi-Fi performance can be degraded because of the following categories.For each category, a different action has to be taken to improve things:

-   -   Power Save settings of the Station        -   Change power save setting of the station    -   Sharing the medium (properly) with other Wi-Fi devices        -   Use another channel that is less occupied (or prioritize            Wi-Fi traffic properly using    -   e.g. Wi-Fi Multimedia priorities (WMM, IEEE 802.11e)    -   Interference at Transmitter side        -   Change to channel without interference (or remove            interference source)    -   Interference at Receiver side        -   Change to channel without interference (or remove            interference source)    -   Physics: high path loss, impossibility to set up multiple        spatial streams        -   move AP or station

The problem to solve is to have an application that can correctlyanalyze Wi-Fi performance issues and indicate the correct categorycausing the issue, so that the end user can be guided to a suitablecorrective action.

SUMMARY

The method for analyzing a wireless link of a wireless node of acustomer premises equipment device during operation of the CPE devicecomprises: performing an active test, during which a data transmissionis forced through the wireless link, to obtain a first set ofparameters, and performing before or after the active test a passivetest, which is a monitoring mode during which a data transmission of theCPE device is monitored, to obtain a second set of parameters. Inparticular, based on the first set of parameters, it is determinedwhether and to which extent the wireless link is in an uncertainty zone,and based on the second set of parameters, the decision is made toassign an observed decrease in a measured data rate (TrainedPhyRate) tophysics effects or to Far End Interference effects.

In an aspect of the invention, the TrainedPhyRate is determined by anactive test, during which the wireless link is fully loaded.

In another aspect of the invention, during the passive test, samples ofone or several of the following parameters are measured in a timeinterval: Received Signal Strength (RSSI), modulation rate (PhysicalLayer Rate) and/or the number of spatial streams used for the wirelesslink, and an average for that parameters is calculated over the testinterval by including a filtering of said parameters to avoid artefactscaused by power save mechanisms.

In a preferred embodiment, the passive test follows immediately theactive test, and/or the active test follows immediately the passivetest, without any pause.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present disclosure are explained in moredetail below by way of example with reference to schematic drawings,which show:

FIG. 1 a system illustrating an access point communicating with astation via a wireless communication,

FIG. 2 a chart illustrating data rates of a wireless communicationaccording to FIG. 1,

FIG. 3 a test application including a coordinator for an active test anda monitor for a passive test,

FIG. 4 a chart illustrating two sets of measured data for IEEE 802.11n2×2 streams between an AP and a STA in an interference-free environment,

FIG. 5 the chart of FIG. 4, including categories for the data rates, and

FIG. 6 test results being displayed on a display as consecutive blocksforming a semi-circle.

DESCRIPTION OF PREFERRED EMBODIMENTS

It should be understood that the elements shown in the figures may beimplemented in various forms of hardware, software or combinationsthereof. Preferably, these elements are implemented in a combination ofhardware and software on one or more appropriately programmedgeneral-purpose devices, which may include a processor, memory andinput/output interfaces. Herein, the phrase “coupled” is defined to meandirectly connected to or indirectly connected with through one or moreintermediate components. Such intermediate components may include bothhardware and software based components.

The present description illustrates the principles of the presentdisclosure. It will thus be appreciated that those skilled in the artwill be able to devise various arrangements that, although notexplicitly described or shown herein, embody the principles of thedisclosure and are included within its scope.

All examples and conditional language recited herein are intended forinstructional purposes to aid the reader in understanding the principlesof the disclosure and the concepts contributed by the inventors tofurthering the art, and are to be construed as being without limitationto such specifically recited examples and conditions.

Moreover, all statements herein reciting principles, aspects, andembodiments of the disclosure, as well as specific examples thereof, areintended to encompass both structural and functional equivalentsthereof. Additionally, it is intended that such equivalents include bothcurrently known equivalents as well as equivalents developed in thefuture, i.e., any elements developed that perform the same function,regardless of structure.

Thus, for example, it will be appreciated by those skilled in the artthat the block diagrams presented herein represent conceptual views ofillustrative circuitry embodying the principles of the disclosure.Similarly, it will be appreciated that any flow charts, flow diagrams,state transition diagrams, pseudocode, and the like represent variousprocesses which may be substantially represented in computer readablemedia and so executed by a computer or processor, whether or not suchcomputer or processor is explicitly shown.

The functions of the various elements shown in the figures may beprovided through the use of dedicated hardware as well as hardwarecapable of executing software in association with appropriate software.When provided by a processor, the functions may be provided by a singlededicated processor, by a single shared processor, or by a plurality ofindividual processors, some of which may be shared. Moreover, explicituse of the term “processor” or “controller” should not be construed torefer exclusively to hardware capable of executing software, and mayimplicitly include, without limitation, digital signal processor (“DSP”)hardware, read only memory (“ROM”) for storing software, random accessmemory (“RAM”), and nonvolatile storage.

Other hardware, conventional and/or custom, may also be included.Similarly, any switches shown in the figures are conceptual only. Theirfunction may be carried out through the operation of program logic,through dedicated logic, through the interaction of program control anddedicated logic, or even manually, the particular technique beingselectable by the implementer as more specifically understood from thecontext.

In the claims hereof, any element expressed as a means for performing aspecified function is intended to encompass any way of performing thatfunction including, for example, a) a combination of circuit elementsthat performs that function or b) software in any form, including,therefore, firmware, microcode or the like, combined with appropriatecircuitry for executing that software to perform the function. Thedisclosure as defined by such claims resides in the fact that thefunctionalities provided by the various recited means are combined andbrought together in the manner which the claims call for. It is thusregarded that any means that can provide those functionalities areequivalent to those shown herein.

In the following description, example methods for analyzing a wireless(Wi-Fi) link of a wireless node of a customer-premises equipment device(CPE) are described, as well as respective devices performing themethods. For purposes of explanation, various specific details are setforth in order to provide a thorough understanding of preferredembodiments. It will be evident, however, to one skilled in the art thatthe present principles may be practiced without these specific details.

A CPE device includes, but is not limited to, in an embodiment aprocessor, e.g. a microprocessor, a memory, in which an operating systemis stored for the operation of the CPE device, a wireless node for awireless operation, and a broadband connection, e.g. an xDSL connection.The wireless node includes, but is not limited to, a complex softwaredriver, a physical layer with data buffers, and an antenna. A CPE deviceof this kind is for example an access gateway, e.g. a residentialgateway, which has a central position within a wireless local areanetwork (WLAN).

The wireless node is controlled by the software driver, which executes anumber of background tasks during operation of the wireless node, e.g.dynamic rate adaptation, packet aggregation, channel quality monitoring,and the like. On top of signal manipulations, the software driver alsoembeds an IEEE 802.11 protocol stack with an associated IEEE definedmanagement and control messaging. The software driver will hence injecta number of management and control packets into the data stream, makingit difficult to analyze a link by transparently looking at the dataframe exchange only.

An arrangement illustrating a wireless communication is schematicallydepicted in FIG. 1: An access point 1 communicates with a station 2 viaa wireless link 3. The access point 1 includes a circuit comprising amicroprocessor 10, a memory 11, a wireless node 12 for the wirelesscommunication, and a test application 13.

The station 2 includes a second circuit comprising a microprocessor 20,a memory 21, a wireless node 22 for the wireless communication, and atest application 23. The wireless node 12 includes a physical layer 14and a link layer 15, and the wireless node 22 includes a physical layer24 and a link layer 25. The access point 1 is for example a residentialgateway establishing with the station 2 a home network of an end-user.

The test application 13 comprises instructions for the microprocessor 10and the test application 23 comprises instructions for themicroprocessor 20, which instructions are included for diagnosing thewireless link 3 and which gather an information set about the wirelesslink 3. The information set includes in particular achievable data rate,physical layer data rate, multiple spatial streams, channel bandwidth,medium availability and a Received Signal Strength Indicator (RSSI).These data can be gathered in a passive mode, in which a datatransmission is monitored between the access point 1 and the station 2or vice versa, or in an active mode, in which a data transmission isforced between the access point 1 and the station 2.

In the active mode, the test application 13 in the access point 1 istrying to push as many data as possible through the wireless link 3 tothe station 2 during a specific test period. In order to avoid anyartefacts, the test application 13 is situated purely at a Media AccessControl (MAC) layer (layer 2). For this active test, no functionality isrequired at the station 2: according to Wi-Fi unicast frameacknowledgements, the test application 13 in the gateway canautonomously measure the layer 2 data rate during the active test. Thistakes care of testing the Wi-Fi performance, which is only one step.

FIG. 2 illustrates the possibilities which have to be considered whendiagnosing the Wi-Fi performance of the access point 1 and the station2. An unidirectional link 3′ from the access point 1 to the station 2 isexamined in this embodiment. A theoretical maximum data rate 30 for thislink is given by the capabilities of the access point 1 and the station2, called here MaxNegotiatedPhyRate or MaxPhyRate, which is for example130 MB/s, in case of IEEE 802.11n with 20 MHz channel bandwidth and twospatial streams (and no short guard interval) is selected for thetransmission between the access point 1 and the station 2. This is thusthe maximum achievable link speed, 100%, which is only a theoreticalvalue. This is taken as a reference for the tested performance as wellas for the different categories of performance. The maximum availablephysical layer rate for the transmission between the access point 1 andthe station 2, MaxPhyRate 30, as negotiated, can be obtained byincluding the maximum available data rates for the IEEE standards802.11b, 802.11g and 802.11n as a function of the number of spatialstreams (MIMO Configuration), channel bandwidth (20 or 40 MHz), and SGI(Short Guard Interval) enabled or not enabled.

In practice, for most situations, physical limitations come into play:the received signal strength RSSI at the station side is reduced forexample due to the distance between the access point 1 and the station 2and a path loss due to any walls or other obstacles and reflections.Also the number of spatial streams has to be determined. The practicallyattainable physical layer rate 31 in ideal conditions and in the absenceof any interference, called here PhysLimitsPhyRate, is therefore lessthan the maximum data rate 30.

Further performance can be lost due to interference on the station 2side, which is not seen by the access point 1, called here far endinterference FEIF: this can be any microwave source like RF Babyphone,microwave oven or a hidden Wi-Fi node, and leads to a further reduceddata rate, called here TrainedPhyRate 32. Similar interference canappear at the access point 1, called here near end interference NEIF:This will reduce the available data rate 32 to a data rate 33. Furtherperformance can be lost by sharing the medium with other Wi-Fi traffic.This is caused in particular by Wi-Fi traffic in the home network causedby other stations of the end-user. This reduced data rate 34 is calledhere AvailableThroughputPSoff describing the available data throughputwith power save modus: off. Another reduction of the data rate can becaused by performance lost due to any power save mode, for example apower save mode implemented in a mobile device, e.g. a smartphone actingas the station 2: Some percentage of its time, the station 2 may be in asleeping mode, called her % PS 35. The final data rate 36 is the finalresult that the end-user can get as the real data rate from the accesspoint 1 to the station 2, called here ThroughputPSon 36.

In order to monitor the data traffic of the physical layer, the layer 1of the OSI (Open Systems Interconnection Model) model, the traffic thatis transmitted and received by the Wi-Fi node of the access point 1, thetest application 13 of the access point 1 receives all received andtransmitted packets. The test application 13 has access to the followingblocks:

-   -   Transmit (TX) packet queue, TX packets    -   Receive (RX) packet queue, RX packets    -   Transmit/Receive signal indicators (RSSI values)

The test application 13 is illustrated in FIG. 3 as a “Diagnozer”, whichis a coordinator for an active test and a monitor for a passive test,and converts received data and link speeds in percentages and presentsthe results to the end-user. The test application 13 is connected via adata bus 41 with a statistics provider 42 included in the access point 1and a statistics provider 43 included in the station 2. The data bus 41uses for example a publish/subscribe messaging system for an exchange ofcontrol commands and data with the statistics providers 42 and 43.

The test application 13 requests a test request 44 or a scan request 45,which are submitted via the data bus 41 to the statistics providers 42,43. The test request 44 can be a passive monitoring test or an activetest. Via the scan request 45, a scan list 47 with recognizedneighboring WLAN nodes is requested from the access point 1 and/or thestation 2. The statistics providers 42, 43 provide test stateinformation 46 and provide, when required, the scan list 47, whichincludes all neighboring WLAN nodes being recognized when the accesspoint 1 and/or the station 2 scan the WLAN channels, and “Wi-Fi Stats”,measured data rates and other statics data 48 being obtained by thetests.

The data provided in this embodiment by the statistics provider 42,called here also transmit (TX) member, include in particular measureddata rates: MaxPhyRate 30, PhysLimitsPhyRate 31, TrainedPhyRate 32,MediumBusy, MediumBusyOtherWi-Fi 33, % PS 35, ThroughputPSon 36, etc.The data transmitted by the statistics provider 43, called here alsoreceive (RX) member, include in particular RSSI and the scan list.

The test request 44 as published via the data bus 41 by the testapplication 13 includes further a test identification number(TestRequest.id), MAC addresses of receive member and transmit member,(sourceMAC, destinationMAC), test type: ping test or layer 2 test,configuration, etc. The test can be a normal test, in which the receivemember is a statistics provider and publishes for example stationstatistics to the test application 13. The test can be also a blindtest, in which the receive member is an associated station not providingany statistics, and the transmit member executes a test autonomously. Inthis case, the test application 13 can use information only from theaccess point 1, the transmit member. The scan request 45 is an event andpublished by the test application 13. The scan list 47 is a state and ispublished by everyone having subscribed to the scan request 45.

For the statistics being provided by an active test, the testmeasurements are synchronized between the access point 1 and the station2. For a passive monitoring, synchronization is not required.

The statistics providers 42, 43 publish locally aggregated statisticsvia the data bus 41, for example every 30 sec in case of passivemonitoring, except when interrupted by an active test. In case ofpassive monitoring, the station 2 samples RSSI and receive data ratesevery second and calculates a filtered RSSI average over the testduration, for example 30 sec. The filtering includes for example athreshold of 1 kbps, or any value between 1 kbps and 10 Mbps, and RSSIsamples are dropped if the receive data rate is below the threshold. TheRSSI samples are aggregated, when the receive data rate is above thatthreshold.

For the passive monitoring, it is further important to separate issuesat the receiver side from CCA (Clear Channel Assessment) related issues.There the fact can be used that the rate adaptation algorithm in anyWLAN node aims at reducing packet loss by stepping down to lowermodulation rates and less spatial streams. If we define “TrainedPhyRate”32 as the modulation rate that is used when the link is trained, we canapproximatively assume that problems on the receive side:packet loss isminimal at this physical layer rate.

Further performance loss can be caused by the CCA mechanism blocking thetransmitter to send packets. This can be assessed by using the CCAstatistics: medium busy/medium busy other Wi-Fi 33. Actual availableperformance can be assessed through CCA statistics and knowledge of theTrainedPhyRate 32, or through an active test.

Medium sharing may cause further performance loss: WLAN is using ashared medium concept based on a CSMA-CA (Carrier Sense MultipleAccess/Collision Avoidance) medium access method. The performance willdrop if more devices are sharing the medium. More difficult is todistinguish what is causing the problems on the receiver side, i.e.interference: then the end-user should change the Wi-Fi channel; orphysics: then the end-user should move the access point 1 or the station2.

Also interference may cause performance loss: The connection speed dropsdue to the presence of interference. Instead of SNR (signal to noiseratio), SiNR (signal to interference noise ratio) applies which impactseither the physical layer rate or the medium availability. Performanceloss is also caused by physics limitations: The connection speed dropsdue to SNR degradation and a reduced ability to use multiple spatialstreams (MIMO: multiple-input and multiple-output). It is noted thatMIMO systems leverage on the ability to use a multitude of spatialstreams in order to achieve high link speeds.

The PhysLimitsPhyRate 31, FIG. 2, can be understood as the boundarybetween performance lost due to physical effects (“physics”) andperformance lost due to interference at the receiver side.PhysLimitsPhyRate 31 is partly defined by extrapolating what physicallayer rate would be used in dependence of the measured signal strength(RSSI)—in the absence of interference. This extrapolation may be basedfor example on reference measurements in a clean environment: this canbe in a conducted set up or in a radiated set up. This covers alsoperformance lost due to high path loss, leading to a low signalstrength.

The maximum available physical layer rate for the transmission betweenthe access point 1 and the station 2, MaxPhyRate 30, as negotiated, canbe obtained for example from table 1 below, which includes the maximumavailable data rates for the IEEE standards 802.11b, 802.11g and 802.11nas a function of the number of spatial streams (MIMO Configuration),channel bandwidth (20 or 40 MHz), and SGI (Short Guard Interval), beingenabled or not enabled.

TABLE 1 802.11b 1 × 1:1 11 NA NA NA 802.11g 1 × 1:1 54 NA NA NA 802.11n1 × 1:1 65  72.2 135 150 802.11n 2 × 2:2 130 144.4 270 300 802.11n 3 ×3:3 195 216.7 405 450 802.11n 4 × 4:4 260 288.9 540 600

For applying the method, advantageously two parts are provided: a testapplication running on client devices (Android, iOS, PC, etc. . . . )and a test application running on the gateway (AP). When using both,optimum measurement results are obtained at both ends of the wirelesslink by reading critical values from the software drivers. In particularthe following data are considered by the method: Path loss and multiplespatial streams for determining physical limitations; non-WLANinterference: at Transmit-side or at Receiver-side; WLAN traffic fromneighbouring WLANs; Rate Adaption, depending on RSSI; and RSSI.

The active test includes in particular the following steps: Step 1:Launches Ping Test from AP to STA, e.g. an Android device, having thegoals: Goal1: wake up TX and RX members before TX test, and Goal2: solvenumber of spatial streams dilemma by checking RX and TX physical rate(PhyRate) at the AP; Step 2: Launches Active layer 2 (L2) TX test fromAP to STA; and Step 3: Display categories in percent on a graphical userinterface (GUI), see for example FIG. 6, described below. These stepsare described in more detail in a previous patent application WO2015/044343, which is incorporated herein by reference.

For calculating losses of a wireless link of a Wi-Fi node between acustomer premises equipment device and a station in a correct mannerduring the passive monitoring test, it is in particular important totake samples of one or several of the following parameters in a definedtime interval, e.g. every second: Received Signal Strength (RSSI),Modulation rate (TrainedPhyRate) and/or the number of spatial streamsused for a given Wi-Fi link, and calculating an average for thatparameters by including a filtering of said parameters. The filtering isused in particular to filter out non-data frames, e.g. control frames,which do not contribute to the Wi-Fi transmission rate.

The method described relies amongst others on the availability ofreference data, in an interference-free environment, related to the RSSIas well as of the Modulation rate (TrainedPhyRate) and the number ofSpatial Streams used for a given Wi-Fi link to define the boundarybetween performance lost due to physical effects and performance lostdue to interference at the receiver side. But it is not trivial task toobtain the correct statistics, as there are mechanisms, e.g. the powersave mechanisms, in place that influence the above mentioned parametersin such a way that they cannot be used as such to understand the qualityof the Wi-Fi link. E.g. a Wi-Fi implementation can reduce the number ofspatial streams and/or the modulation rate to reduce power consumption,rather than in reaction to interference, which would prohibit the use ofmultiple spatial streams and/or of higher modulation rates. When doingan active test, —by forcing data traffic through the Wi-Fi link, mostimplementations will abandon these power-save actions, and a normalaveraging of the above-mentioned parameters will provide—in mostcases—accurate statistics that yield a correct quality assessment of theWi-Fi link.

In case of a passive, Wi-Fi quality monitoring, however, such an activetest is to be avoided. So for such passive monitoring tools, a way tocollect adequate statistics that can avoid power save artefacts isneeded. How to achieve that is described in the patent application WO2015/044343. The method described involves filtering of the samplestaken so as to retain only the meaningful samples for calculating theaverage of the relevant parameters.

The main problem with the current state of the art relates to theboundary between performance lost due to physical effects andperformance lost due to interference at the receiver side. As describedabove, reference data in an interference-free environment are used todefine this boundary. The problem is that there is a large degree ofuncertainty if these reference data are recorded in realisticenvironments. FIG. 4 shows two sets of measured reference data for IEEE802.11n 2×2 streams between an AP and a STA, measured at two differentdays, in an interference-free environment and for different conditionsof path loss, that demonstrate this uncertainty: in particular theTrainedPhyRates from AP to STA in a region between a RSSI values of −55to −75 dBm vary between 70 Mbps and 120 Mbps.

This uncertainty is not a test problem or a test artefact. It is areflection of the different RF channel conditions of the Wi-Fi link.Time and frequency dispersion in the RF channel between transmitter andreceiver can distort the signal on receiver side, resulting in a lowerTrainedPhyRate as compared to what can be expected for a given RSSI incase of a perfect RF channel, e.g. in conducted measurements. Anotherphysical effect is related to spatial streams. Depending on the presenceof multiple RF paths between transmitter and receiver, i.e. depending onwhether reflections of the direct RF path between transmitter andreceiver exist, it can be possible—or not—to set up multiple spatialstreams even without the presence of any interference.

A remaining problem to solve is therefore to assign the decrease of theTrainedPhyRate, as compared to what can be achieved for a given RSSI inperfect conditions, to either physical effects, i.e. lack of reflectionsand channel conditions, or to far-end interference, i.e. externalinterference on the receiver side lowering the Received Signal to Noiseand Interference Ratio, for those test measurements that are in thisuncertainty zone.

First step of the analysis is to separate issues at receiver side fromCCA related issues. There we can use the fact the rate adaptationalgorithm in any Wi-Fi node aims at reducing packet loss by steppingdown to lower modulation rates and less spatial streams. If we define“TrainedPhyRate” as the modulation rate that is used when the link istrained, we can approximatively assume that problems on receiveside/packet loss is minimal at this PhyRate.

Further performance loss can be caused by the CCA mechanism blocking thetransmitter to send packets. This can be assessed by using the CCAstatistics (medium busy/medium busy other Wi-Fi). Actual availableperformance can be assessed through CCA statistics and knowledge ofTrained PhyRate, or through an active test.

More difficult is to distinguish what is causing the problems onreceiver side (i.e. interference>change channel; or physics>move AP orSTA). For this, we define PhysLimitsPhyRate as the boundary betweenperformance lost due to “physics” and performance lost due tointerference at receiver side. PhysLimitsPhyRate is partly defined byextrapolating what PhyRate would be used in case of the measured signalstrength (RSSI)—in the absence of interference. This extrapolation isbased on reference measurements in a clean environment—this can be in aconducted set up or in a radiated set up.

This covers performance lost due to high path loss, low signal strength.

The second factor defining PhysLimitsPhyRate is related to thepossibility to set up multiple spatial streams or not. Depending on theenvironment, presence or absence of multiple reflections/spatial paths,(de-)correlation of the signal seen by the different receivers. To takethis into account, we use the measured average number of spatial streamsas used by the link under traffic.

The above method can be improved by additionally performing —before orafter the active test—a passive test, which is a monitoring mode duringwhich a data transmission of the CPE device is monitored, to obtain asecond set of parameters. In particular, based on the first set ofparameters, it is determined whether and to which extent the wirelesslink is in an uncertainty zone, and based on the second set ofparameters, the decision is made to assign an observed decrease in ameasured data rate (TrainedPhyRate) to physics effects or to Far EndInterference effects.

For a preferred embodiment, the improvement can be summarized with thefollowing steps:

-   -   Determine the uncertainty zone of the TrainedPhyRate as        depending on the RSSI values, as described with regard to        FIG. 4. This can be broken down into Modulation Rate/Spatial        Stream versus RSSI, number of Spatial Streams versus RSSI, usage        of SGI (Short Guard Interval) versus RSSI. Alternatively, the        TrainedPhyRate can be considered as a combination of the above.    -   An active test is executed by the transmitter to obtain the        TrainedPhyRate of a given Wi-Fi link, during which the Wi-Fi        link is fully loaded. During this test, a first set of relevant        parameters is recorded: in partiular RSSI, PhyRate/MCS values,        and number of spatial streams used.    -   Immediately before and/or after the active test, the transmitter        passively records a second set of relevant parameters.    -   Based on the first set of parameters, it is determined whether        and to which extent the tested link is in the uncertainty zone.    -   Based on the second set of parameters, the decision is made to        assign the observed decrease of the TrainedPhyRate to Physical        effects or to Far End Interference.

The active test is needed to fully execute the link and get reliablevalues of TrainedPhyRate, RSSI etc. This active test will also yield thereal, rather than an extrapolated, data rate that can be achieved overthis Wi-Fi link. However, during the active test, it is impossible toaccurately sense the medium and listen to signs of interference: mainlyCCA statistics like medium availability, glitches, etc.,—referring tothe analogy that you cannot listen while talking. The second set ofparameters solves this problem and allows to use the “signatures”observed while sensing the medium to distinguish “Far End Interference”issues from “Physics”.

In more detail, according to a preferred embodiment with reference toFIG. 5, the method includes:

-   -   Determine the uncertainty zone in “TrainedPhyRate” versus “RSSI”        correlation. This can be broken down into the determination of:        Modulation Rate/Spatial Stream versus RSSI, number of Spatial        Streams versus RSSI, usage of SGI (Short Guard Interval) versus        RSSI. Alternatively “Trained PhyRate” can be considered as a        combination of the above.    -   Referring to FIG. 5, “TxPhyRate”: The depicted measurement        points are reference data, Trained TxPhyRate versus RSSI,        recorded in an interference-free environment on two different        days: 20130716 and 20130718. Line 81, “conducted”, shows the        maximum theoretical TxPhyRate “MaxPhyRate” versus RSSI in a        perfect conducted environment. Obviously, below −65 dBm, the        conducted results are not representative for even the best        radiated measurement points. Therefore, a “top” boundary is        used, line 82, and a “bottom” boundary, line 83, on the edges of        the reference measurement points, to define the uncertainty        zone.

The performance loss represented by the difference between “MaxPhyRate”,line 81, and the top boundary, line 82, is called “% SureBlueRegion”,region 84, corresponding with an area between 30 and 31 of FIG. 6, andis always assigned to physical effects. The performance loss representedby the region below line 83, difference between “RedBorderPhyrate”, and“TrainedPhyRate”, line 32 of FIG. 2, is called “SureRedRegion”, region85, corresponding with the area between 31-32 of FIG. 6, and is alwaysassigned to interference. The area between the bottom boundary 83 andthe top boundary 82 is called “PurpleRegion”, region 86, which is theuncertainty region.

-   -   An active test is executed by the transmitter to obtain the        TrainedPhyRate 32 of a given Wi-Fi link, during which the Wi-Fi        link is fully loaded. During this test, the first set of        relevant parameters are recorded, amongst others, RSSI, PhyRate        and MCS values, and number of spatial streams used.    -   Immediately before and/or after the active test, the transmitter        passively records the second set of parameters while generating        a some amount of uplink and downlink traffic. This can be done        for example by providing a ping test.    -   Based on the first set of parameters, it is determined whether        and to which extent the tested link is in the uncertainty zone        86, e.g. within RSSI values of −75 dBm and −55 dBm, as depicted        in FIG. 5. The first set of parameters yields all info needed to        assess the performance factors impacting the transmitter side of        the Wi-Fi link, i.e. power save effects, sharing the medium,        near end interference, as well as the main parameter to        distinguish transmitter side and receiver side, i.e. Trained        PhyRate, and the proper RSSI value. The top boundary 82 can be        calculated directly from the observed RSSI value.    -   Based on the second set of parameters, the decision is made to        assign the observed decrease in TrainedPhyRate 32 to “Physics”        or to “Far End Interference”.    -   The first part of this decision lies in correcting the bottom        boundary 83 with information regarding the ratio of average        number of spatial streams uplink versus downlink, as recorded in        the second set of parameters. This is because the asymmetric        nature of the active test will not provide an accurate view on        the uplink. This correction shifts the bottom boundary 83, in        case the ratio of average number of spatial streams Uplink        versus Downlink indicates Far End Interference, i.e. a lower        average number of spatial streams Downlink. The second part        consists of assigning the uncertainty region 86 to Far End        Interference, in case the CCA statistics in the second set of        parameters indicate the presence of near end interference, i.e.        % of time that the medium is not used and is not available above        a certain threshold, e.g. 5% of time.

The method described relies on the availability of correct statisticsrelated to the quality of the Wi-Fi link, such as but not limited toSignal Strength (RSSI) as well as of the Modulation rate (Physical Rate)and the number of Spatial Streams used for a given Wi-Fi link. It is nota trivial task to obtain the correct statistics, as there are power savemechanisms in place that influence the above mentioned parameters insuch a way that they cannot be used as such to understand the quality ofthe Wi-Fi link. E.g. a Wi-Fi implementation can reduce the number ofspatial streams and/or the modulation rate to reduce powerconsumption—rather than in reaction to interference which would prohibitthe use of multiple spatial streams and/or of higher modulation rates.

When doing an active test—i.e. forcing traffic through the Wi-Fi link,most implementations will abandon these power-save actions, and a normalaveraging of the above-mentioned parameters will provide—in mostcases—accurate statistics that yield a correct quality assessment of theWi-Fi link. In case of a passive, Wi-Fi quality monitoring, however,such an active test is to be avoided. So for such passively monitoringtools, a way was found to collect adequate statistics that can avoidpower save artefacts.

The passive monitoring test takes samples of the above-mentionedparameters on a short time scale, e.g. every second. Rather than takingjust the average of the samples taken over a certain interval—averagingis certainly needed to obtain reliable results—a filtered average isused. This means that only those samples are retained for calculatingthe average that are taken at moment when sufficient traffic is flowingover the link. This can be deduced from the TxRate and RxRate parametersthat are also sampled every second. By taking the correct threshold forthe TxRate and/or RxRate messurement, the filtered average can avoid theartefacts caused by power save mechanisms, and ensure that onlycorrectly “trained” values of the relevant parameters such as PhyRate,RSSI, and number of spatial streams are considered.

The obtained results can be displayed for a user on a display of hisstation 2 by the test application 13 for example as consecutive blocksforming a semi-circle, as shown in FIG. 6. The data rates as explainedwith regard to FIG. 2 define the length of each block. A pointer Pvisualizes the finally attainable data rate 36, which is in thisembodiment 23% of the theoretically available data rate of 130 MB/s.Each of the blocks include a question mark Q, which can be selected bythe user for example by using a mouse or a touchpad. By selecting one ofthe question marks Q, the user is informed about the problem whichcauses the throughput loss leading to the contribution of this block andgives an advice for the user, how he can improve the situation. In caseof selecting the question mark Q of the block 50, the user is informedthat the obtained data rate during the test was only 28 MB/s, 23% of thetheoretically maximum rate of 130 MB/s.

Although embodiments which incorporate the teachings of the presentdisclosure have been shown and described in detail herein, those skilledin the art can readily devise many other varied embodiments that stillincorporate these teachings. Having described preferred embodiments(which are intended to be illustrative and not limiting), it is notedthat modifications and variations can be made by persons skilled in theart in light of the above teachings. It is therefore to be understoodthat changes may be made in the particular embodiments of the disclosuredisclosed which are within the scope of the disclosure.

1. Method for analyzing a wireless link of a wireless node of a customer premises equipment (CPE) device, comprising performing a first test, during which a data transmission is forced through the wireless link, to obtain a first set of parameters, and performing a second test, which is a monitoring mode during which a data transmission of the wireless link is monitored, to obtain a second set of parameters.
 2. The method of claim 1, wherein, based on the first set of parameters, it is determined whether and to which extent the wireless link is in an uncertainty zone, and based on the second set of parameters, the decision is made to assign an observed decrease in a measured data rate, called “TrainedPhyRate”, to Physics effects or to a Far End Interference.
 3. The method of claim 2, wherein the uncertainty zone determined from the measured TrainedPhyRate, is depending on measured RSSI values, the TrainedPhyRate being measured by the first test, during which the wireless link is fully loaded, and the decision to assign an observed decrease in TrainedPhyRate to Physics effects or to Far End Interference is made with reference to measured RSSI values as included in the second set of parameters. 4-6. (canceled)
 7. The method according to claim 1, comprising taking samples of one or several of the following parameters in a time interval: Received Signal Strength (RSSI), modulation rate (Physical Layer Rate) and/or the number of spatial streams used for the wireless link during the second test, and calculating an average for that parameters over the test interval by including a filtering of said parameters to avoid artefacts caused by power save mechanisms.
 8. The method of claim 7, comprising: sample the transmission rate (TxRate) and receive rate (RxRate) in said time interval to calculate the traffic flowing over the link, and retaining only those parameter values, Received Signal Strength, modulation rate and/or the number of spatial streams, for calculating the average, that are taken at a moment when sufficient traffic is flowing over the link. 9-10. (canceled)
 11. The method of claim 7, wherein the average parameters are used for calculating the maximum possible data rate for the wireless link, e.g. a Wi-Fi transmission of a given arrangement of two devices (PhysLimitsPhyRate). 12-13. (canceled)
 14. The method of claim 1, comprising: using test measurements in a reference environment, e.g. clean environment without any interference sources in selected wireless channels.
 15. The method of claim 14, wherein the maximum obtainable wireless data rate is determined by determining the data throughput from the test measurements for a given measured received signal strength (RSSI) and by taking into account a correction factor for the number of multiple spatial streams for a selected wireless standard used for the transmission.
 16. The method of claim 15, wherein the number of multiple spatial streams is determined by checking the Rx and/or TX physical rate at the access point side or station side.
 17. The method of claim 15, wherein a correction factor is determined to distinguish between environment and interference by taking into account the number of spatial streams used for the access point to the station link in comparison with the number of spatial streams for the station to the access point link. 18-20. (canceled)
 21. Device comprising a processor, a memory and a wireless node, said processor being configured to perform: a first test, during which a data transmission is forced through the wireless link, to obtain a first set of parameters, and a second test, which is a monitoring mode during which a data transmission of the wireless link is monitored, to obtain a second set of parameters.
 22. A non-transitory program storage medium, readable by a computer and comprising executable program code for performing a method in accordance with claim
 1. 23. An application comprising executable program code for performing a method in accordance with claim
 1. 24. The device according to claim 21, wherein, based on the first set of parameters, the processor determines whether and to which extent the wireless link is in an uncertainty zone, and based on the second set of parameters, the processor decides to assign an observed decrease in a measured data rate, called “TrainedPhyRate”, to Physics effects or to a Far End Interference.
 25. The device according to claim 24, wherein the uncertainty zone determined from the measured TrainedPhyRate, is depending on measured RSSI values, the TrainedPhyRate being measured by a first test, during which the wireless link is fully loaded, and the decision to assign an observed decrease in TrainedPhyRate to Physics effects or to Far End Interference is made with reference to measured RSSI values as included in the second set of parameters. 